Informações sobre o curso
3.9
469 classificações
145 avaliações
Programa de cursos integrados
100% online

100% online

Comece imediatamente e aprenda em seu próprio cronograma.
Prazos flexíveis

Prazos flexíveis

Redefinir os prazos de acordo com sua programação.
Nível intermediário

Nível intermediário

Horas para completar

Aprox. 29 horas para completar

Sugerido: 5 weeks of study, 5-7 hours/week...
Idiomas disponíveis

Inglês

Legendas: Inglês

Habilidades que você terá

Bayesian StatisticsBayesian Linear RegressionBayesian InferenceR Programming
Programa de cursos integrados
100% online

100% online

Comece imediatamente e aprenda em seu próprio cronograma.
Prazos flexíveis

Prazos flexíveis

Redefinir os prazos de acordo com sua programação.
Nível intermediário

Nível intermediário

Horas para completar

Aprox. 29 horas para completar

Sugerido: 5 weeks of study, 5-7 hours/week...
Idiomas disponíveis

Inglês

Legendas: Inglês

Programa - O que você aprenderá com este curso

Semana
1
Horas para completar
1 hora para concluir

About the Specialization and the Course

This short module introduces basics about Coursera specializations and courses in general, this specialization: Statistics with R, and this course: Bayesian Statistics. Please take several minutes read this information. Thanks for joining us in this course!...
Reading
1 vídeo (total de (Total 2 mín.) min), 4 leituras
Reading4 leituras
About Statistics with R Specialization10min
About Bayesian Statistics10min
Pre-requisite Knowledge10min
Special Thanks2min
Horas para completar
6 horas para concluir

The Basics of Bayesian Statistics

<p>Welcome! Over the next several weeks, we will together explore Bayesian statistics. <p>In this module, we will work with conditional probabilities, which is the probability of event B given event A. Conditional probabilities are very important in medical decisions. By the end of the week, you will be able to solve problems using Bayes' rule, and update prior probabilities.</p><p>Please use the learning objectives and practice quiz to help you learn about Bayes' Rule, and apply what you have learned in the lab and on the quiz. ...
Reading
9 vídeos (total de (Total 41 mín.) min), 2 leituras, 3 testes
Video9 videos
Conditional Probabilities and Bayes' Rule2min
Bayes' Rule and Diagnostic Testing6min
Bayes Updating2min
Bayesian vs. frequentist definitions of probability4min
Inference for a Proportion: Frequentist Approach3min
Inference for a Proportion: Bayesian Approach7min
Effect of Sample Size on the Posterior2min
Frequentist vs. Bayesian Inference9min
Reading2 leituras
Module Learning Objectivess
Week 1 Lab Instructionss
Quiz3 exercícios práticos
Week 1 Lab12min
Week 1 Practice Quiz20min
Week 1 Quiz20min
Semana
2
Horas para completar
7 horas para concluir

Bayesian Inference

In this week, we will discuss the continuous version of Bayes' rule and show you how to use it in a conjugate family, and discuss credible intervals. By the end of this week, you will be able to understand and define the concepts of prior, likelihood, and posterior probability and identify how they relate to one another....
Reading
10 vídeos (total de (Total 45 mín.) min), 2 leituras, 3 testes
Video10 videos
From the Discrete to the Continuous5min
Elicitation6min
Conjugacy4min
Inference on a Binomial Proportion5min
The Gamma-Poisson Conjugate Families6min
The Normal-Normal Conjugate Families3min
Non-Conjugate Priors4min
Credible Intervals3min
Predictive Inference4min
Reading2 leituras
Module Learning Objectivess
Week 2 Lab Instructionss
Quiz3 exercícios práticos
Week 2 Lab28min
Week 2 Practice Quiz20min
Week 2 Quiz40min
Semana
3
Horas para completar
8 horas para concluir

Decision Making

In this module, we will discuss Bayesian decision making, hypothesis testing, and Bayesian testing. By the end of this week, you will be able to make optimal decisions based on Bayesian statistics and compare multiple hypotheses using Bayes Factors. ...
Reading
14 vídeos (total de (Total 75 mín.) min), 2 leituras, 3 testes
Video14 videos
Losses and decision making3min
Working with loss functions6min
Minimizing expected loss for hypothesis testing5min
Posterior probabilities of hypotheses and Bayes factors6min
The Normal-Gamma Conjugate Family6min
Inference via Monte Carlo Sampling3min
Predictive Distributions and Prior Choice5min
Reference Priors7min
Mixtures of Conjugate Priors and MCMC6min
Hypothesis Testing: Normal Mean with Known Variance7min
Comparing Two Paired Means Using Bayes' Factors6min
Comparing Two Independent Means: Hypothesis Testing3min
Comparing Two Independent Means: What to Report?5min
Reading2 leituras
Module Learning Objectivess
Week 3 Lab Instructionss
Quiz3 exercícios práticos
Week 3 Lab22min
Week 3 Practice Quiz16min
Week 3 Quiz40min
Semana
4
Horas para completar
8 horas para concluir

Bayesian Regression

This week, we will look at Bayesian linear regressions and model averaging, which allows you to make inferences and predictions using several models. By the end of this week, you will be able to implement Bayesian model averaging, interpret Bayesian multiple linear regression and understand its relationship to the frequentist linear regression approach. ...
Reading
11 vídeos (total de (Total 72 mín.) min), 2 leituras, 3 testes
Video11 videos
Bayesian simple linear regression8min
Checking for outliers4min
Bayesian multiple regression4min
Model selection criteria5min
Bayesian model uncertainty7min
Bayesian model averaging7min
Stochastic exploration8min
Priors for Bayesian model uncertainty8min
R demo: crime and punishment9min
Decisions under model uncertainty7min
Reading2 leituras
Module Learning Objectivess
Week 4 Lab Instructionss
Quiz3 exercícios práticos
Week 4 Lab22min
Week 4 Practice Quiz20min
Week 4 Quiz40min
3.9
145 avaliaçõesChevron Right
Direcionamento de carreira

17%

comecei uma nova carreira após concluir estes cursos
Benefício de carreira

14%

consegui um benefício significativo de carreira com este curso

Melhores avaliações

por RRSep 21st 2017

Great course. Difficult to apprehend sometimes as the Frequentist paradigm is learned first but once you get it, it is really amazing to see the believe update in action with data.

por GHApr 10th 2018

I like this course a lot. Explanations are clear and much of the (unnecessarily heavyweight) maths is glossed over. I particularly liked the sections on Bayesian model selection.

Instrutores

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Mine Çetinkaya-Rundel

Associate Professor of the Practice
Department of Statistical Science
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David Banks

Professor of the Practice
Statistical Science
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Colin Rundel

Assistant Professor of the Practice
Statistical Science
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Merlise A Clyde

Professor
Department of Statistical Science

Sobre Duke University

Duke University has about 13,000 undergraduate and graduate students and a world-class faculty helping to expand the frontiers of knowledge. The university has a strong commitment to applying knowledge in service to society, both near its North Carolina campus and around the world....

Sobre o Programa de cursos integrados Statistics with R

In this Specialization, you will learn to analyze and visualize data in R and create reproducible data analysis reports, demonstrate a conceptual understanding of the unified nature of statistical inference, perform frequentist and Bayesian statistical inference and modeling to understand natural phenomena and make data-based decisions, communicate statistical results correctly, effectively, and in context without relying on statistical jargon, critique data-based claims and evaluated data-based decisions, and wrangle and visualize data with R packages for data analysis. You will produce a portfolio of data analysis projects from the Specialization that demonstrates mastery of statistical data analysis from exploratory analysis to inference to modeling, suitable for applying for statistical analysis or data scientist positions....
Statistics with R

Perguntas Frequentes – FAQ

  • Ao se inscrever para um Certificado, você terá acesso a todos os vídeos, testes e tarefas de programação (se aplicável). Tarefas avaliadas pelos colegas apenas podem ser enviadas e avaliadas após o início da sessão. Caso escolha explorar o curso sem adquiri-lo, talvez você não consiga acessar certas tarefas.

  • Quando você se inscreve no curso, tem acesso a todos os cursos na Especialização e pode obter um certificado quando concluir o trabalho. Seu Certificado eletrônico será adicionado à sua página de Participações e você poderá imprimi-lo ou adicioná-lo ao seu perfil no LinkedIn. Se quiser apenas ler e assistir o conteúdo do curso, você poderá frequentá-lo como ouvinte sem custo.

  • We assume you have knowledge equivalent to the prior courses in this specialization.

  • No. Completion of a Coursera course does not earn you academic credit from Duke; therefore, Duke is not able to provide you with a university transcript. However, your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile.

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